nlp学习的基础教材，共583页，内含目录。

An Introduction to this Course Definitions & classifications of research, and research procedures The concept of variables Quantitative research design Questionnaire survey Item analysis,validity & reliability Data exploring Descriptive statistics Inferential statistics Writing a research proposal Reporting a research Research evaluation

Data sources: primary, secondary Objectives: descriptive, exploratory, correlational, explanatory Time for data collection: cross-sectional, longitudinal (panel, trend) Data types: qualitative, quantitative (survey, experimental) Primary: studies based on primary, or original, data sources, such as classroom observations or real students, or their test scores, or their responses to a questionnaire. Secondary: studies based on secondary sources such as other researhers’ books and articles, including library research and literature reviews. Descriptive: studies involving the collection of data in order to test hypotheses or to answer questions concerning the current status of the subjects of the study. Exploratory: studies conducted into an issue or problem where there are few or no earlier studies to refer to. The focus is on gaining insights and familiarity for later investigation. Correlational: The basic question for descriptive research is - "What are the values of a number of variables for a given sample of subjects. The basic research question for correlation research is - What is the relationship between two or more variables for a given set of subjects. Notice that we said relationship between variables and not the effect of one variable on another variable. In descriptive research we are just describing our subjects in terms of one or more variables, while in correlational research we are looking at the relationship between the variables. Correlational: The basic question for descriptive research is - "What are the values of a number of variables for a given sample of subjects. The basic research question for correlation research is - What is the relationship between two or more variables for a given set of subjects. Notice that we said relationship between variables and not the effect of one variable on another variable. In descriptive research we are just describing our subjects in terms of one or more variables, while in correlatio

Functions of a research proposal Planning tool for the researcher Rough draft of the final research report Convincing others that your research is worth undertaking Demonstrating expertise and competency in your particular area of study

单样本t检验 独立样本t检验 配对样本t检验 单因素方差分析 Normal distribution and sampling distribution Normal distribution is made up of individual scores. Sampling distribution is composed of group means. With more groups means, a curve of their distribution would be symmetric. This symmetric curve is not called a normal distribution but rather a sampling distribution of means A sampling distribution is the distribution of a sample statistic that would be obtained if all possible samples of the same size were drawn from a given population.

Pearson Correlation The Pearson correlation allows us to establish the strength of relationships between continuous variables. To show the relationship, the first step is to draw a scatterplot or scattergram, which can help us to obtain a preliminary understanding of this relationship. The scatterplot can be described in terms of direction, strength and linearity. Correlation and SPSS Pearson product-moment coefficient is designed for interval level (continuous) variables. It can also be used if you have one continuous variable (e.g., scores on a measure of self-esteem) and one dichotomous variable (e.g., sex: M/F). Spearman rank order correlation is designed for use with ordinal level or ranked data. SPSS will calculate two types of correlation. First, it will give a simple bivariate correlation (which just means between two variables), also known as zero-order correlation. SPSS will also explore the relationship between two variables, while controlling for another variable. This is known as partial correlation.

本资源包含中国计算语言学大会CCL2019上的报告PPT，列表如下： 表示学习-张岳、多模态-魏忠钰、郭毅可-数据高效性机器学习、机器翻译-冯洋、句法分析-屠可伟、人机对话-严睿、社交媒体-丁效、信息抽取-陈玉博、信息检索-任昭春、许晶晶-基于对抗训练的机器学习鲁棒性分析、张晓东-人工智能：从历史看未来。

Applied Linguistics

Altmann-Fitter是一款用于对频次分布进行单变量离散概率分布拟合的软件，在所有的实证研究领域都能使用。它内置了超过200种概率分布及其相关属性的信息，这是目前所能找到的最大的分布集之一。该软件拟合操作的自动化程度很高，用户基本上无须设定初始值或其他参数。其拟合优度的标准是基于卡方检验。拟合过程是以迭代的方式进行的，程序会不断提高拟合优度，直至找不到更好的拟合结果为止。该软件为收费软件，其最新版本为3.1.0版。试用版除了不能导出数据之外，其他的功能与收费版都是一样的。 因此，软件的试用版就已经可以用于实际研究了。

北京大学常宝宝老师的计算语言学课件，一共12个pdf文件